Date of Award

8-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Civil Engineering

Committee Member

Dr. Qiushi Chen, Committee Chair

Committee Member

Dr. Charng Hsein Juang

Committee Member

Dr. Ronald D. Andrus

Committee Member

Dr. Stephen M. Moysey

Abstract

Soil liquefaction is a major cause of damage during earthquakes that could trigger many kinds of ground failures such as ground settlement, lateral spreading, land slides, etc. These ground failures could cause damage to infrastructures such as buildings, bridges, and lifelines resulting in significant economic losses. Therefore it is of significant importance to assess liquefaction hazard. The triggering and consequencing ground failure of liquefaction have been well investigated in the past decades. Nowadays, the dominant approach that correlates the observed field behavior with various in-situ "œindex" tests is able to achieve considerably precise assessments for free field conditions at site-specific scale. Regional scale assessments of liquefaction hazard, however, are still underdeveloped. Issues such as cross-geologic units correlations are still not systematically investigated in regional liquefaction assessment. Therefore, the main objective of this dissertation is to develop a solution framework for reliable regional assessment of earthquake-induced liquefaction hazard. Another objective is to validate this framework by applying it to several earthquake-prone regions so that liquefaction hazard maps of these regions could be added to the literature and guide designers, engineers and researchers. Moreover, the dominant method of estimating liquefaction damages via empirical correlations are not capable for complex site conditions. Therefore another objective of this dissertation is to study alternative approaches for general estimation of liquefaction damages. To achieve these objectives, a multiscale modeling framework for better estimate of regional liquefaction hazard with material randomness and heterogeneity is developed. One advantage the developed methodology is the extension of conventional random field models to account for soil spatial variability at multiple scales and resolutions. The method allows selectively and adaptively generating random fields at smaller scales around critical areas or around areas where soil properties are known to a great detail from lab or field tests. The process is defined such that spatial correlation is consistent across length scales. Illustrative examples (Marina District in San Francisco, Alameda County in California, and Christchurch in New Zealand) are presented. Liquefaction hazard is evaluated at multi-scale. Compared with single scale analyses, multi-scale random fields provide more detailed information and higher-resolution soil properties around critical areas. This framework provides a new way to consistently incorporating small-scale local liquefaction analysis into large-scale liquefaction assessment mapping. Furthermore, finite element method is identified as a prominent alternative to traditional approach for liquefaction estimation via empirical correlations. A dynamic FEM model is built upon which an effective stress analysis is performed to estimate liquefaction-induced soil deformation at site-specific scale. It is shown the developed finite element model as a numerical tool can be used in predicting cyclic liquefaction in soils. This research is expected to shed light on the complete understanding of soil liquefaction during earthquakes in hoping of saving economic losses in the future.

Share

COinS